Since there has been no transformer-based baseline for unsupervised ReID, the state-of-the-art CNN-based framework C-Contrast [1]} is selected for the following experiments. We reproduce C-Contrast with ResNet50 and ViT-S/16 on both USL ReID and UDA ReID https://github.com/alibaba/cluster-contrast-reid. All results are reproduced using the official code with the same random seed and GPU machine to reduce randomness.. Based on observations made from Table REF , we choose MoCoV2 for ResNet50 and DINO for ViT-S/16 in this section in Table REF . SSL pre-training doesn't provide large gains compared with Sup when applied with ResNet50, not to mention that performance drop is observed on MSMT17. This is consistent with the aforementioned conclusion that Transformer is more sensitive to the pre-training than CNN. In contrast, SSL pre-training on LUPerson improves the performance by a large margin for ViT-S/16. The UDA performance on MS2MA and MA2MS also yields the similar conclusion.
